Prenatal alcohol exposure (PAE) alters the structure and function of specific brain regions, and these alterations correspond with cognitive, behavioral and neurophysiological deficits; however very little is known about how structural and functional connectivity among regions may be altered. Enhanced understanding of how developmental trajectories are altered in individuals with a Fetal Alcohol Spectrum Disorder (FASD) is essential for the timing and design of specialized interventions, and for identifying sensitive periods during which maximal benefits may be achieved. Ultimately, early interventions can help improve healthy development of brain networks, and produce a more beneficial developmental trajectory. Structural (diffusion tensor imaging) and functional (resting state functional MRI) brain connectivity will be assessed using multimodal neuroimaging techniques in FASD youth and age-matched control participants. Moreover, despite accumulating evidence from animal models, nothing is yet known about how these trajectories of brain development and connectivity differ between FASD boys and girls. It also remains to be investigated if the effects of PAE on altering hormone systems is involved with brain abnormalities in FASD boys and girls. Thus, the present proposal aims to use a multimodal imaging approach to assess sex differences in the effects of PAE on brain connectivity. The proposed research project will assess hormone function in PAE boys and girls, and hormones will be integrated with measures of structural and functional brain connectivity. Integrated brain and hormone measures will be correlated with measures of cognitive performance (WISC-IV). The proposed findings have implications for cognitive, behavioral and mental health problems that occur at a high prevalence among individuals with an FASD. Results will help identify sexually dimorphic effects of PAE on underlying neural networks in order to inform future intervention and treatment strategies targeted to a specific sex and specific impairments in neural networks. Enhanced interventions applied during key developmental time periods may help relieve the burden on health care systems by preventing/reducing a range of health problems later in life.